Routing Strategies Based on Macroscopic Fundamental Diagram

Abstract

Traffic management can prevent too many vehicles in a traffic network from reducing traffic performance. In particular, traffic can be routed so that the bottlenecks are not oversaturated. The macroscopic fundamental diagram provides a relationship between the number of vehicles and network performance. Traffic control can be applied on this level to overcome the computational complexity of networkwide control with traditional control levels of links or vehicles. The main questions are (a) how effective traffic control is with aggregate variables compared with full information and (b) whether the shape of the macroscopic fundamental diagram changes under traffic control. A grid network with periodic boundary conditions is used as an example and is split into several subnetworks. The following routing strategies are compared: the shortest paths in distance and time (dynamic due to congestion) and approximations of the path shortest in time but calculated with only variables aggregated for a subnetwork and of the path shortest in time but calculated with only subnetwork accumulation. For the third and fourth routing strategies, only information aggregated over the subnetwork is used. The results show improved traffic flow with detailed information. Effective control is also possible by using aggregated information, but only with the right choice of a subnetwork macroscopic fundamental diagram. Furthermore, when detailed information is used to optimize—and therefore in a subnetwork—the macroscopic fundamental diagram changes.